Comment[ArrayExpressAccession] E-GEOD-54006 MAGE-TAB Version 1.1 Public Release Date 2014-02-14 Investigation Title Massively parallel single-cell RNA-Seq for dissecting cell type and cell state compositions Comment[Submitted Name] Massively parallel single-cell RNA-Seq for dissecting cell type and cell state compositions Experiment Description In multi-cellular organisms, biological function emerges when cells of heterogeneous types and states are combined into complex tissues. Nevertheless unbiased dissection of tissues into coherent cell subpopulations is currently lacking. We introduce an automated, massively parallel single cell RNA sequencing method for intuitively analyzing in-vivo transcriptional states in thousands of single cells. Combined with unsupervised classification algorithms, it facilitates ab initio and marker-free characterization of classical hematopoietic cell types from splenic tissues. Importantly, modeling single cells transcriptional states in dendritic cells subpopulations, where a cell type hierarchy is difficult to define with marker-based approaches, uncovers complex combinatorial activity of multiple gene modules and capture cell-to-cell variability in steady state conditions and following pathogen activation. Massively parallel single cell RNA-seq thereby emerges as an effective tool for unbiased dissection of complex tissues. CD11c+ enriched splenocyte mRNA profiles from single cells were generated by deep sequencing of thousands of single cells, sequenced in several batches in an Illumina Hiseq 2000 The 'umitab.txt' processed data file contains the mRNA counts (post-filtering RMT counts) of a gene per each well (columns) The 'experimental_design.txt' contains a detailed information regarding each well. The 'readme0421.txt' was provided with details about each supplementary file. Term Source Name ArrayExpress EFO Term Source File http://www.ebi.ac.uk/arrayexpress/ http://www.ebi.ac.uk/efo/efo.owl Person Last Name Amit Amit Tanay Jaitin Kenigsberg Keren-Shaul Person First Name Ido Ido Amos Diego Ephraim Hadas Person Email ido.amit@weizmann.ac.il Person Affiliation Weizmann Institute of Science Person Phone 972-8-9343338 Person Address Immunology, Weizmann Institute of Science, 234 Herzl st., Rehovot, Israel Person Roles submitter Protocol Name P-GSE54006-4 P-GSE54006-1 P-GSE54006-3 P-GSE54006-2 Protocol Description Illumina Casava1.8 software used for basecalling. Sequences with RMT of low quality (defined as RMT with minimum Phred score of less than 27) were filtered out. Single cell pool-barcode and well-barcode-RMT were extracted from the first and second end of the read (paired-end reads), respectively, and added to the fastq header, under the barcode field, delimited by a hyphen, i.e. POOL_BARCODE-WELL_BARCODE-RMT, where NNNNNN was used as a place holders if pool barcode was not used. Reads were separated by POOL_BARCODE:WELL_BARCODE header data, allowing 1 sequencing error. This process created a single fastq file for each source well. The umitab.txt file contains ~4,590 sample data columns. Each of these samples corresponds to a single cell transcriptome profile. They are distributed among the 28 raw data files. Each such raw data file contains reads corresponding to between 96 and 192 single cells. In the umitab.txt file, each column/cell name begins with a pool (batch) number. Each pool corresponds to one of the 28 raw data files. Genome_build: mm9 Supplementary_files_format_and_content: tab-delimited text files contain mRNA molecule count values for each single cell; Rows represent gene symbols of UCSC-known genes. Underscore delimited row names correspond to known gene entries with non-unique gene symbol. Columns represent single-cell measurements and named as BATCH-ID_CELL-ID. Batch details can be found in the sample description. For samples 13 to 28, mice were injected with 1 µg LPS (samples 15, 16, 19, 20, 23, 24, 27 and 28) or PBS (phosphate buffered saline; control mouse; samples 13, 14, 17, 18, 21, 22, 25 and 26) 2 hours before splen extraction (2h treatment). Each mouse was euthanized and spleen removed, homogenized to single cell suspension, red cells removed by selective lysis, and for all samples except for samples 11 and 12, the cell suspensions were enriched for CD11c-positive cells with anti-mouse CD11c antibodies coupled to magentic beads and the MACS system. single cell RNA-seq for gene expression quantitation: 3' end mRNA libraries were prepared for sequencing using a method developed at Dr. Ido Amit's lab, Weizmann Institute of Science 12 to 15 weeks-old mice housed at the Weizmann Institute animal facility Protocol Type normalization data transformation protocol sample treatment protocol nucleic acid library construction protocol growth protocol Experimental Factor Name TREATMENT SELECTION MARKER Experimental Factor Type treatment selection marker Publication Title Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Publication Author List Jaitin DA, Kenigsberg E, Keren-Shaul H, Elefant N, Paul F, Zaretsky I, Mildner A, Cohen N, Jung S, Tanay A, Amit I PubMed ID 24531970 Publication DOI 10.1126/science.1247651 Comment[SecondaryAccession] GSE54006 Comment[GEOReleaseDate] 2014-02-14 Comment[ArrayExpressSubmissionDate] 2014-01-12 Comment[GEOLastUpdateDate] 2014-05-27 Comment[AEExperimentType] RNA-seq of coding RNA Comment[AdditionalFile:Data1] GSE54006_experimental_design.txt Comment[AdditionalFile:Data2] GSE54006_readme0421.txt Comment[AdditionalFile:Data3] GSE54006_umitab.txt Comment[SecondaryAccession] SRP035326 Comment[SequenceDataURI] http://www.ebi.ac.uk/ena/data/view/SRR1106612-SRR1106639 SDRF File E-GEOD-54006.sdrf.txt